Background

Several studies have tested the reliability of Risk Terrain Modelling (RTM) by focusing on different geographical contexts and types of crime or events. However, to date, there has been no attempt to systematically review the evidence on whether RTM is effective at predicting areas at high risk of events. This paper reviews RTM’s efficacy as a spatial forecasting method.

Methods

We conducted a systematic review and meta-analysis of the RTM literature. We aggregated the available data from a sample of studies that measure predictive accuracy and conducted a proportion meta-analysis on studies with appropriate data.

Results

In total, we found 25 studies meeting the inclusion criteria. The systematic review demonstrated that RTM has been successful in identifying at risk places for acquisitive crimes, violent crimes, child maltreatment, terrorism, drug related crimes and driving while intoxicated (DWI). The proportion meta-analysis indicated that almost half of future cases in the studies analysed were captured in the top ten per cent of risk cells. This typically covers a very small portion of the full study area.

Conclusions

The study demonstrates that RTM is an effective forecasting method that can be applied to identify places at greatest risk of an event and can be a useful tool in guiding targeted responses to crime problems.

中文翻译：

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作为空间预测方法的风险地形建模 (RTM) 的系统回顾和元分析

背景

多项研究通过关注不同的地理环境和犯罪或事件类型来测试风险地形建模 (RTM) 的可靠性。然而，迄今为止，还没有尝试系统地审查关于 RTM 是否有效预测事件高风险区域的证据。本文回顾了 RTM 作为一种空间预测方法的功效。

方法

我们对 RTM 文献进行了系统回顾和荟萃分析。我们从测量预测准确性的研究样本中汇总了可用数据，并对具有适当数据的研究进行了比例荟萃分析。

结果

我们总共发现了 25 项符合纳入标准的研究。系统审查表明，RTM 已成功识别出获得性犯罪、暴力犯罪、虐待儿童、恐怖主义、与毒品有关的犯罪和醉酒驾驶 (DWI) 的危险场所。比例荟萃分析表明，在所分析的研究中，近一半的未来病例被捕获在前 10% 的风险单元中。这通常涵盖整个研究区域的很小一部分。

结论

该研究表明，RTM 是一种有效的预测方法，可用于识别事件风险最大的地方，并可成为指导针对犯罪问题做出有针对性的反应的有用工具。